A remote speech-based AI system to screen for early Alzheimer's disease via smartphones.

ABSTRACT:

Introduction

Artificial intelligence (AI) systems leveraging speech and language changes could support timely detection of Alzheimer's disease (AD).

Methods

The AMYPRED study (NCT04828122) recruited 133 subjects with an established amyloid beta (Aβ) biomarker (66 Aβ+, 67 Aβ-) and clinical status (71 cognitively unimpaired [CU], 62 mild cognitive impairment [MCI] or mild AD). Daily story recall tasks were administered via smartphones and analyzed with an AI system to predict MCI/mild AD and Aβ positivity.

Results

Eighty-six percent of participants (115/133) completed remote assessments. The AI system predicted MCI/mild AD (area under the curve [AUC] = 0.85, ±0.07) but not Aβ (AUC = 0.62 ±0.11) in the full sample, and predicted Aβ in clinical subsamples (MCI/mild AD: AU

SUBMITTER: Fristed E 

PROVIDER: S-EPMC9632864 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature